INTRODUCTION AND OBJECTIVE:
Different nomograms exist for the preoperative prediction of pelvic lymph-node metastatic disease in individual patients with prostate cancer (PCa). These nomograms do not incorporate modern staging imaging techniques such as prostate-specific membrane antigen (PSMA)-positron emission tomography (PET). The aim of this study, was to determine the predictive performance of the Briganti 2017, the Memorial Sloan Kettering Cancer Center (MSKCC), and the Briganti 2019-nomograms with the addition of PSMA-PET in an international, multicenter present-day cohort of patients undergoing robot-assisted radical prostatectomy (RARP) and extended pelvic lymph-node dissection (ePLND) for localized PCa.
All 1156 eligible patients who underwent RARP and ePLND in three reference centers for PCa surgery between January 2016 and November 2020 were included. Performance of the three nomograms was assessed using the receiver operating characteristic (ROC) curve derived area under the curve (AUC), calibration plots and decision curve analyses. Subsequently, recalibration and addition of PSMA-PET to the nomograms were performed.
Overall, 273/1156 patients (24%) had pelvic lymph-node metastatic (pN1) disease on histopathological examination. AUCs of the Briganti 2017, the MSKCC, and the Briganti 2019-nomograms were 0.70 (95%Confidence Interval (95%CI): 0.64-0.76), 0.71 (95%CI: 0.65-0.77) and 0.77 (95%CI: 0.70-0.82), respectively. PSMA-PET findings showed a significant association with pN1-disease when added to the nomograms (p<0.001). Addition of PSMA-PET substantially improved the discriminative ability of the models yielding cross-validated AUCs of 0.76 (95%CI: 0.70-0.82), 0.78 (95%CI: 0.70-0.82) and 0.82 (95%CI: 0.75-0.86), respectively. In decision curve analyses, the addition of PSMA-PET to the three existing nomograms resulted in increased net-benefits.
The addition of PSMA-PET to the previously developed nomograms showed a substantially improved predictive performance, which suggests that PSMA-PET is a likely future candidate for a modern predictive nomogram.
Source of Funding:
No funding was received for conducting this study